Positivity-preserving and elementary stable nonstandard method for a COVID-19 SIR model

IF 0.6 Q3 MATHEMATICS
D. Conte, N. Guarino, G. Pagano, B. Paternoster
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引用次数: 3

Abstract

The main purpose of this work is to build a numerical method for solving an epidemiological model that describes the spread of COVID-19 in some countries. The method is constructed using a NonStandard Finite Difference (NSFD) discretization for the analyzed model, in order to preserve its positivity and equilibrium points properties. Numerical simulations testify the best performance of the proposed scheme with respect to the related Standard Finite Difference (SFD) method, the famous explicit four-stage order-four Runge-Kutta known as RK4, and another positivity-preserving nonstandard method. © 2022, Padova University Press. All rights reserved.
COVID-19 SIR模型的保正初等稳定非标准方法
这项工作的主要目的是建立一种数值方法来求解描述COVID-19在一些国家传播的流行病学模型。该方法对分析模型采用非标准有限差分(NSFD)离散化,以保持模型的正性和平衡点性质。数值模拟结果表明,该方法与相关的标准有限差分(SFD)方法、著名的显式四阶四阶龙格-库塔方法(RK4)以及另一种保正非标准方法相比具有最佳性能。©2022,帕多瓦大学出版社。版权所有。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.70
自引率
7.70%
发文量
0
审稿时长
8 weeks
期刊介绍: Dolomites Research Notes on Approximation is an open access journal that publishes peer-reviewed papers. It also publishes lecture notes and slides of the tutorials presented at the annual Dolomites Research Weeks and Workshops, which have been organized regularly since 2006 by the Padova-Verona Research Group on Constructive Approximation and Applications (CAA) in Alba di Canazei (Trento, Italy). The journal publishes, on invitation, survey papers and summaries of Ph.D. theses on approximation theory, algorithms, and applications.
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